Biased Estimation of Adjusted Odds Ratios From Incomplete Covariate Data Due to Violation of the Missing at Random Assumption

We investigate the possible bias due to an erroneous missing at random assumption if adjusted odds ratios are estimated from incomplete covariate data using the maximum likelihood principle. A relation between complete case estimates and maximum likelihood estimates allows us to identify situations where the bias vanishes. Numerical computations demonstrate that the bias is most serious if the degree of the violation of the missing at random assumption depends on the value of the outcome variable or of the observed covariate. Implications for the analysis of prospective and retrospective studies are given

The response of a small stream in the Lesni potok forested catchment, central Czech Republic, to a short-term in-stream acidification

International audienceLesni Potok stream drains a forested headwater catchment in the central Czech Republic. It was artificially acidified with hydrochloric acid (HC1) for four hours to assess the role of stream substrate in acid-neutralisation and recovery. The pH was lowered from 4.7 to 3.2. Desorption of Ca and Mg and desorption or solution of Al dominated acid-neutralisation; Al mobilisation was more important later. The stream substrate released 4,542 meq Ca, 1,184 meq Mg, and 2,329 meq Al over a 45 m long and 1 m wide stream segment; smaller amounts of Be, Cd, Fe, and Mn were released. Adsorption of SO42- and desorption of F? occurred during the acidification phase of the experiment. The exchange reactions were rapidly reversible for Ca, Mg and SO42-; but not symmetric as the substrate resorbed 1083, 790 and 0 meq Ca, Mg, and Al, respectively, in a 4-hour recovery period. Desorption of SO42-; occurred during the resorption of Ca and Mg. These exchange and dissolution reactions delay acidification, diminish the pH depression and retard recovery from episodic acidification. The behaviour of the stream substrate-water interaction resembles that for soil?soil water interactions. A mathematical dynamic mass-balance based model, MASS (Modelling Acidification of Stream pediments), was developed which simulates the adsorption and desorption of base cations during the experiment and was successfully calibrated to the experimental data. Keywords: Al, Ca, Mg, base cations, acid-neutralisation, stream acidification, recovery, stream sediment, experiment, modelling, adsorption, desorption, adsorption, Czech Republic, Lesni Poto

Influence of magnetic fields on magneto-aerotaxis

The response of cells to changes in their physico-chemical micro-environment is essential to their survival. For example, bacterial magnetotaxis uses the Earth's magnetic field together with chemical sensing to help microorganisms move towards favoured habitats. The studies of such complex responses are lacking a method that permits the simultaneous mapping of the chemical environment and the response of the organisms, and the ability to generate a controlled physiological magnetic field. We have thus developed a multi-modal microscopy platform that fulfils these requirements. Using simultaneous fluorescence and high-speed imaging in conjunction with diffusion and aerotactic models, we characterized the magneto-aerotaxis of Magnetospirillum gryphiswaldense. We assessed the influence of the magnetic field (orientation; strength) on the formation and the dynamic of a micro-aerotactic band (size, dynamic, position). As previously described by models of magnetotaxis, the application of a magnetic field pointing towards the anoxic zone of an oxygen gradient results in an enhanced aerotaxis even down to Earth's magnetic field strength. We found that neither a ten-fold increase of the field strength nor a tilt of 45° resulted in a significant change of the aerotactic efficiency. However, when the field strength is zeroed or when the field angle is tilted to 90°, the magneto-aerotaxis efficiency is drastically reduced. The classical model of magneto-aerotaxis assumes a response proportional to the cosine of the angle difference between the directions of the oxygen gradient and that of the magnetic field. Our experimental evidence however shows that this behaviour is more complex than assumed in this model, thus opening up new avenues for research

Dose-response relationship between ambulatory load magnitude and load-induced changes in COMP in young healthy adults

To determine the dose-response relationship between ambulatory load magnitude during a walking stress test and load-induced changes in serum concentration of cartilage oligomeric matrix protein (sCOMP) in healthy subjects.; sCOMP was assessed before and after a 30-min walking stress test performed on three test days by 24 healthy volunteers. In each walking stress test, one of three ambulatory loads was applied in a block randomized crossover design: normal body weight (BW) (100%BW = normal load); reduced BW (80%BW = reduced load); increased BW (120%BW = increased load). Knee kinematics and ground reaction force (GRF) were measured using an inertial sensor gait analysis system and a pressure plate embedded in the treadmill.; Load-induced increases in sCOMP rose with increasing ambulatory load magnitude. Mean sCOMP levels increased immediately after the walking stress test by 26.8 ± 12.8%, 28.0 ± 13.3% and 37.3 ± 18.3% for the reduced, normal or increased load condition, respectively. Lower extremity kinematics did not differ between conditions.; The results of this study provide important evidence of a dose-response relationship between ambulatory load magnitude and load-induced changes in sCOMP. Our data suggests that in normal weight persons sCOMP levels are more sensitive to increased than to reduced load. The experimental framework presented here may form the basis for studying the relevance of the dose-response relationship between ambulatory load magnitude and load-induced changes in biomarkers involved in metabolism of healthy articular cartilage and after injury

Clinical Outcomes of Zirconia Dental Implants: A Systematic Review

To determine the survival rate and marginal bone loss (MBL) of zirconia dental implants restored with single crowns or fixed dental prostheses. An electronic search was conducted up to November 2015 (without any restriction regarding the publication time) through the databases MEDLINE (PubMed), Cochrane Library, and EMBASE to identify randomized controlled clinical trials and prospective clinical trials including >15 patients. Primary outcomes were survival rate and MBL. Furthermore, the influence of several covariates on MBL was evaluated. Qualitative assessment and statistical analyses were performed. This review was conducted according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for systematic reviews. With the applied search strategy, 4,196 titles could be identified. After a screening procedure, 2 randomized controlled clinical trials and 7 prospective clinical trials remained for analyses. In these trials, a total of 326 patients received 398 implants. The follow-up ranged from 12 to 60 mo. Implant loss was mostly reported within the first year, especially within the healing period. Thereafter, nearly constant survival curves could be observed. Therefore, separate meta-analyses were performed for the first and subsequent years, resulting in an implant survival rate of 95.6% (95% confidence interval: 93.3% to 97.9%) after 12 mo and, thereafter, an expected decrease of 0.05% per year (0.25% after 5 y). Additionally, a meta-analysis was conducted for the mean MBL after 12 mo, resulting in 0.79 mm (95% confidence interval: 0.73 to 0.86 mm). Implant bulk material and design, restoration type, and the application of minor augmentation procedures during surgery, as well as the modes of temporization and loading, had no statistically significant influence on MBL. The short-term cumulative survival rates and the MBL of zirconia implants in the presented systematic review are promising. However, additional data are still needed to confirm the long-term predictability of these implants

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR

Vascular grading of angiogenesis: prognostic significance in breast cancer

The study aimed to evaluate the prognostic value of angiogenesis by vascular grading of primary breast tumours, and to evaluate the prognostic impact of adding the vascular grade to the Nottingham Prognostic Index (NPI). The investigation included 836 patients. The median follow-up time was 11 years and 4 months. The microvessels were immunohistochemically stained by antibodies against CD34. Angiogenesis was graded semiquantitatively by subjective scoring into three groups according to the expected number of microvessels in the most vascular tumour area. The vascular grading between observers was moderately reproduced (κ = 0.59). Vascular grade was significantly associated with axillary node involvement, tumour size, malignancy grade, oestrogen receptor status and histological type. In univariate analyses vascular grade significantly predicted recurrence free survival and overall survival for all patients (P< 0.0001), node-negative patients (P< 0.0001) and node-positive patients (P< 0.0001). Cox multivariate regression analysis showed that vascular grading contributed with independent prognostic value in all patients (P< 0.0001). A prognostic index including the vascular grade had clinical impact for 24% of the patients, who had a shift in prognostic group, as compared to NPI, and implied a better prognostic dissemination. We concluded that the angiogenesis determined by vascular grading has independent prognostic value of clinical relevance for patients with breast cancer. © 2000 Cancer Research Campaig

Comparison of methods for handling missing data on immunohistochemical markers in survival analysis of breast cancer

Background:Tissue micro-arrays (TMAs) are increasingly used to generate data of the molecular phenotype of tumours in clinical epidemiology studies, such as studies of disease prognosis. However, TMA data are particularly prone to missingness. A variety of methods to deal with missing data are available. However, the validity of the various approaches is dependent on the structure of the missing data and there are few empirical studies dealing with missing data from molecular pathology. The purpose of this study was to investigate the results of four commonly used approaches to handling missing data from a large, multi-centre study of the molecular pathological determinants of prognosis in breast cancer.Patients and Methods:We pooled data from over 11 000 cases of invasive breast cancer from five studies that collected information on seven prognostic indicators together with survival time data. We compared the results of a multi-variate Cox regression using four approaches to handling missing data-complete case analysis (CCA), mean substitution (MS) and multiple imputation without inclusion of the outcome (MI) and multiple imputation with inclusion of the outcome (MI). We also performed an analysis in which missing data were simulated under different assumptions and the results of the four methods were compared.Results:Over half the cases had missing data on at least one of the seven variables and 11 percent had missing data on 4 or more. The multi-variate hazard ratio estimates based on multiple imputation models were very similar to those derived after using MS, with similar standard errors. Hazard ratio estimates based on the CCA were only slightly different, but the estimates were less precise as the standard errors were large. However, in data simulated to be missing completely at random (MCAR) or missing at random (MAR), estimates for MI were least biased and most accurate, whereas estimates for CCA were most biased and least accurate.Conclusion:In this study, empirical results from analyses using CCA, MS, MI and MI were similar, although results from CCA were less precise. The results from simulations suggest that in general MI is likely to be the best. Given the ease of implementing MI in standard statistical software, the results of MI and CCA should be compared in any multi-variate analysis where missing data are a problem. © 2011 Cancer Research UK. All rights reserved

Respiratory Infections and Antibiotic Usage in Common Variable Immunodeficiency

BACKGROUND: Patients with common variable immunodeficiency (CVID) suffer frequent respiratory tract infections despite immunoglobulin replacement and are prescribed significant quantities of antibiotics. The clinical and microbiological nature of these exacerbations, the symptomatic triggers to take antibiotics, and the response to treatment have not been previously investigated. OBJECTIVES: To describe the nature, frequency, treatment, and clinical course of respiratory tract exacerbations in patients with CVID and to describe pathogens isolated during respiratory tract exacerbations. METHODS: We performed a prospective diary card exercise in 69 patients with CVID recruited from a primary immunodeficiency clinic in the United Kingdom, generating 6210 days of symptom data. We collected microbiology (sputum microscopy and culture, atypical bacterial PCR, and mycobacterial culture) and virology (nasopharyngeal swab multiplex PCR) samples from symptomatic patients with CVID. RESULTS: There were 170 symptomatic exacerbations and 76 exacerbations treated by antibiotics. The strongest symptomatic predictors for commencing antibiotics were cough, shortness of breath, and purulent sputum. There was a median delay of 5 days from the onset of symptoms to commencing antibiotics. Episodes characterized by purulent sputum responded more quickly to antibiotics, whereas sore throat and upper respiratory tract symptoms responded less quickly. A pathogenic virus was isolated in 56% of respiratory exacerbations and a potentially pathogenic bacteria in 33%. CONCLUSIONS: Patients with CVID delay and avoid treatment of symptomatic respiratory exacerbations, which could result in structural lung damage. However, viruses are commonly represented and illnesses dominated by upper respiratory tract symptoms respond poorly to antibiotics, suggesting that antibiotic usage could be better targeted

Multidimensional severity assessment in bronchiectasis:An analysis of 7 European cohorts.

INTRODUCTION: Bronchiectasis is a multidimensional disease associated with substantial morbidity and mortality. Two disease-specific clinical prediction tools have been developed, the Bronchiectasis Severity Index (BSI) and the FACED score, both of which stratify patients into severity risk categories to predict the probability of mortality. METHODS: We aimed to compare the predictive utility of BSI and FACED in assessing clinically relevant disease outcomes across seven European cohorts independent of their original validation studies. RESULTS: The combined cohorts totalled 1612. Pooled analysis showed that both scores had a good discriminatory predictive value for mortality (pooled area under the curve (AUC) 0.76, 95% CI 0.74 to 0.78 for both scores) with the BSI demonstrating a higher sensitivity (65% vs 28%) but lower specificity (70% vs 93%) compared with the FACED score. Calibration analysis suggested that the BSI performed consistently well across all cohorts, while FACED consistently overestimated mortality in 'severe' patients (pooled OR 0.33 (0.23 to 0.48), p<0.0001). The BSI accurately predicted hospitalisations (pooled AUC 0.82, 95% CI 0.78 to 0.84), exacerbations, quality of life (QoL) and respiratory symptoms across all risk categories. FACED had poor discrimination for hospital admissions (pooled AUC 0.65, 95% CI 0.63 to 0.67) with low sensitivity at 16% and did not consistently predict future risk of exacerbations, QoL or respiratory symptoms. No association was observed with FACED and 6 min walk distance (6MWD) or lung function decline. CONCLUSION: The BSI accurately predicts mortality, hospital admissions, exacerbations, QoL, respiratory symptoms, 6MWD and lung function decline in bronchiectasis, providing a clinically relevant evaluation of disease severity